Bayesian Inference Based Robust Computing on Memristor Crossbar
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Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9585997/9586083/09586160.pdf?arnumber=9586160
Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Bringing uncertainty quantification to the extreme-edge with memristor-based Bayesian neural networks;Nature Communications;2023-11-20
2. Improving Realistic Worst-Case Performance of NVCiM DNN Accelerators Through Training with Right-Censored Gaussian Noise;2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD);2023-10-28
3. Tolerating Device-to-Device Variation for Memristive Crossbar-Based Neuromorphic Computing Systems: A New Bayesian Perspective;2023 International Joint Conference on Neural Networks (IJCNN);2023-06-18
4. Resist: Robust Network Training for Memristive Crossbar-Based Neuromorphic Computing Systems;IEEE Transactions on Circuits and Systems II: Express Briefs;2023-06
5. Countering Uncertainties in In-Memory-Computing Platforms with Statistical Training, Accuracy Compensation and Recursive Test;2023 Design, Automation & Test in Europe Conference & Exhibition (DATE);2023-04
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